• Design and implement scalable distributed systems that handle heavy CPU, disk, and network workloads. • Architect systems for high throughput, reliability, and efficient resource utilization. • Develop distributed algorithms and data processing pipelines. • Analyze system behavior to identify bottlenecks across compute, storage, and network layers. • Optimize workloads for maximum efficiency and minimal resource waste. • Develop strategies for parallelization, batching, and workload scheduling. • Implement system components and tooling primarily in Python and Bash. • Build custom orchestration, automation, and distributed job execution mechanisms. • Write efficient algorithms and low-level logic to manage large-scale workloads. • Build instrumentation, metrics, and telemetry to measure system performance. • Develop dashboards and analysis workflows to guide optimization decisions. • Use empirical data and experimentation to improve system behavior. • Design systems that operate reliably across distributed environments. • Implement monitoring, debugging, and recovery mechanisms for large-scale systems. • Collaborate with infrastructure and platform teams to ensure smooth deployment and operation.